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21/10/2017, · Despite the improved accuracy of deep ,neural networks,, the discovery of adversarial examples has raised serious ,safety, concerns. Most existing approaches for crafting adversarial examples necessitate some knowledge (architecture, parameters, etc.) of the ,network, at hand. In this paper, we focus on image classifiers and propose a feature-guided black-box approach to test the ,safety, …
Detecting ,safety helmet, wearing in surveillance videos is an essential task for ,safety, management, compliance with regulations, and reducing the death rate from construction industry accidents. However, it is much challenged by some factors like interocclusion, scale variances, perspective distortion, small object detection, and the carrier ,recognition, of ,safety helmet,.
Safety helmet, wearing detection is very essential in power substation. This paper proposed a innovative and practical ,safety helmet, wearing detection method based on image processing and machine learning. At first, the ViBe background modelling algorithm is exploited to detect motion object under a view of fix surveillant camera in power substation.
22/8/2020, · YOLO is the latest state-of-the-art real-time object detection algorithm. It is a single convolutional ,neural network, that simultaneously predicts multiple bounding boxes and classes of the entire image in the single scan. The framework was developed by . The ,network, architecture was inspired by the GoogLeNet model for image classification .
Safety, Veriﬁcation and Robustness Analysis of ,Neural Networks, via Quadratic Constraints and Semideﬁnite Programming Mahyar Fazlyaby, Manfred Morari, George J. Pappas Abstract—Certifying the ,safety, or robustness of ,neural net-works, against input uncertainties and adversarial attacks is an emerging challenge in the area of safe machine ...
volutional ,neural network, (CNN) is used to select motorcyclists among the moving objects. Again, we apply CNN on upper one fourth part for further ,recognition, of motorcyclists driving without a ,helmet,. The performance of the proposed approach is evaluated on two datasets, IITH ,Helmet, 1 contains sparse
Abstract: Touchless hand gesture ,recognition, systems are becoming important in automotive user interfaces as they improve ,safety, and comfort. Various computer vision algorithms have employed color and depth cameras for hand gesture ,recognition,, but robust classification of gestures from different subjects performed under widely varying lighting conditions is still challenging.